function d = hybridNeuron_AdpC(t, y, params)
    % y = [x; y_val; z; c]
    % 参数结构体 params 包含 a, b, alpha, beta, delta, A, f, k, epsilon
    
    % 变量
    x = y(1);
    y_val = y(2);
    z = y(3);
    c = y(4);
    
    % 提取参数
    a = params.a;
    b = params.b;
    alpha = params.alpha;
    beta = params.beta;
    delta = params.delta;
    % 这里使用周期性输入信号
    A = params.A;
    f = params.f;
    us = A * cos(f * t);  
    k = params.k;
    epsilon = params.epsilon;
    
    % 定义模型方程 (参见 Eq.(5))
    dx = (1 - a)*x - (1/3)*x^3 - y_val + us;
    dy = c * (x - b*sin(beta*z)*y_val);
    dz = delta*y_val - alpha*z;
    
    % 计算能量:
    % 电容能量 H_C = 0.5*x^2
    HC = 0.5*x^2;
    % 总能量 H = 0.5*x^2 + 0.5*(1/c)*y^2 + 0.5*b*z*sin(beta*z)*y
    H = 0.5*x^2 + 0.5*(y_val^2)/c + 0.5*b*z*sin(beta*z)*y_val;
    
    % 阶跃函数 θ(p)：如果 p >= 0 则返回 1，否则返回 0
    theta_val = double(epsilon - abs(HC/H) >= 0);
    
    % 自适应调控方程 (Eq.(11))
    dc = k * c * theta_val;
    
    d = [dx; dy; dz; dc];
end
